Image Spam detection in E-mails using Grasshoppers optimization technique
Deepika Mallampati, Nagaratna P. Hegde · 2023
one of the most frequent types of digital communication is email. Spam is unsolicited mass mail, whereas image spam includes spam text incorporated in images. This type of spam threatens email communications because spammers use it to avoid text spam filters. This paper provides a support vector machine (SVM) based classification algorithm and a biology optimization strategy to categorize emails as spam or ham. In this study, we examine image spam detection strategies using different combinations of image processing and machine learning algorithms. The grasshopper optimization algorithm (GOA) is an approach that statistically models and simulates the behavior of natural locust swarms. We investigate and analyze the performance of Grasshopper optimizations using several evaluation measures, such as accuracy, precision, recall, f1-score, and convergence rate to the global optimum solution.